Jia, Tao

KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.

2012 (English)Doctoral thesis, comprehensive summary (Other academic)

Abstract [en]

The continuous progression of urbanization has resulted in an increasing number of people living in cities or towns. In parallel, advancements in technologies, such as the Internet, telecommunications, and transportation, have allowed for better connectivity among people. This has engendered drastic changes in urban systems during the recent decades. From a social geographic perspective, the changes in urban systems are primarily characterized by intensive contacts among people and their interactions with the surrounding urban environment, which further leads to subsequent challenging problems such as traffic jams, environmental pollution, urban sprawl, etc. These problems have been reported to be heterogeneous and non-deterministic. Hence, to cope with them, massive amounts of geographic data are required to create new knowledge on urban systems.

Due to the thriving of Volunteer Geographic Information (VGI) in recent years, this thesis presents knowledge on urban systems based on extensive VGI datasets from three sources: highway dataset from the OpenStreetMap (OSM) project, photo location dataset from the Flickr website, and GPS tracking datasets from volunteers, taxicabs, and air flights. The knowledge primarily relates to two issues of urban systems: the urban space and the corresponding human dynamics. In accordance, on one hand, urban space acts as a carrier for associated geographic activities and knowledge of it benefits our understanding of current social and economic problems in urban systems. On the other hand, human dynamics reflect human behavior in urban space, which leads to complex mobility or activity patterns. Its investigation allows a derivation of the underlying driving force that is very instructive to urban planning, traffic management, and infectious disease control. Therefore, to fully understand the two issues, this thesis conducts a thorough investigation from multiple aspects.

The first issue is investigated from four aspects. First, at the city level, the controversial topic of city size regularity is investigated in terms of natural cities, and the conclusion is that Zipf’s law holds stably for all US cities. Second, at the sub-city level, the size distribution of spatial units within different cities in terms of the clusters formed by street nodes, photo locations, and taxi static points are explored, and the result shows a remarkable scaling property of these spatial units. Third, enlightened by the scaling property of the urban space at the city or sub-city level, this thesis devises a novel tool that can demarcate the cities into three categories: compact cities, normal cities, and sprawling cities. The tool is then applied to cities in both the US and three European countries. In the last, another representation of urban space is taken into account, namely the transportation network. The findings report that the US airport network displays the properties of scale-free, small-world, and disassortative mixing and that the individual natural airports show heterogeneous patterns that are probably subject to geographic constraints and socioeconomic factors.

The second issue is examined from four perspectives. First, at the city level, the movement flow contributed by agents using two types of behavior is investigated through an agent-based simulation, and the result conjectures that the human mobility behavior is mainly shaped by the underlying street network. Second, at the country level, this thesis reports that the human travel length by air can be approximated well by an exponential distribution, and subsequent simulations indicate that human mobility behavior is largely constrained by the underlying airport network. Third, at the regional level, the length that humans travel by car is demonstrated to agree well with a power law with exponential cutoff distribution, and subsequent simulation further reproduces this levy flight characteristic. Based on the simulation, human mobility behavior is again revealed to be primarily shaped by the underlying hierarchical spatial structure. Finally, taxicab static points are adopted to explore human activity patterns, which can be characterized as the regularities in space and time, the heterogeneity and predictability in space.

From a complex system perspective, this thesis presents the knowledge discovered in urban systems using massive volumes of geographic data. Together with new knowledge from empirical findings, the development of methods, and the design of theoretic models, this thesis also shares the research community with geographic data generated from extensive VGI datasets and the corresponding source codes. Moreover, this study is aligned with a paradigm shift in that it analyzes large-size datasets using high processing power as opposed to analyzing small-size datasets with low processing power.

Tao, Jia

KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.

Bin, Jiang

University of Gävle.

(English)Manuscript (preprint) (Other academic)

Abstract [en]

In this paper, we develop a novel approach to measuring urban sprawl based on street nodes and naturallydefined urban boundaries, both extracted from massive volunteered geographic informationOpenStreetMap databases through some data-intensive computing processes. The street nodes are definedas street intersections and ends, while the naturally defined urban boundaries constitute what we callnatural cities. We find that the street nodes are significantly correlated with population of cities. Based onthis finding, we set street nodes as a proxy of population to measure urban sprawl. We further find thatstreet nodes bear a significant linear relationship with city areal extents. In the plot with the x axisrepresenting city areal extents, and the y axis street nodes, sprawling cities are located below the regressionline. We verified the approach using urban areas and population from the US census, and then applied theapproach to three European countries: France, Germany, and the United Kingdom for the categorization ofnatural cities into three classes: sprawling, compact, and normal. This categorization sets a uniformstandard for cross comparing sprawling levels across an entire country.

Bin, Jiang

Abstract [en]

Urban systems have long been characterized as the scaling property, although there are a lot of argues on the definition and organization of its component or spatial unit. In this paper we propose an entropy-based hierarchical clustering method to aggregate the individual location to form the component or spatial unit. Through the application of the method to three datasets from the different aspects of urban systems, we double check the robustness and consistence of this method. Importantly, it is found that the size of the derived component or spatial unit follows a remarkably power law distribution, which further suggests the scaling property of the underlying urban systems.

Jiang, B.

Abstract [en]

From a complex network perspective, this study sets out two aims around the US airport network (USAN) which is built from en-route location information of domestic flights in the US. First, we analyze the structural properties of the USAN with respect to its binary and weighted graphs, and second we explore the airport patterns, which have wide-ranging implications. Results from the two graphs indicate the following. (1) The USAN exhibits scale-free, small-world and disassortative mixing properties, which are consistent with the mainstream perspectives. Besides, we find (2) a remarkable power relationship between the structural measurements in the binary graph and the traffic measurements in the weighted counterpart, namely degree versus capacity and attraction versus volume. On the other hand, investigation of the airport patterns suggests (3) that all the airports can be classified into four categories based on multiple network metrics, which shows a complete typology of the airports. And it further indicates (4) that there is a subtle relationship between the airport traffic and the geographical constraints as well as the regional socioeconomic indicators.

Bin, Jiang

University of Gävle.

Tao, Jia

University of Gävle.

2011 (English)Article in journal (Other academic) Submitted

Abstract [en]

A range of early studies have been conducted to illustrate human mobility patterns using differenttracking data, such as dollar notes, cell phones and taxicabs. Here, we explore human mobility patternsbased on massive tracking data of US flights. Both topological and geometric properties are examinedin detail. We found that topological properties, such as traffic volume (between airports) and degree ofconnectivity (of individual airports), including both in- and outdegrees, follow a power lawdistribution but not a geometric property like travel lengths. The travel lengths exhibit an exponentialdistribution rather than a power law with an exponential cutoff as previous studies illustrated. Wefurther simulated human mobility on the established topologies of airports with various movingbehaviors and found that the mobility patterns are mainly attributed to the underlying binary topologyof airports and have little to do with other factors, such as moving behaviors and geometric distances.Apart from the above findings, this study adopts the head/tail division rule, which is regularity behindany heavy-tailed distribution for extracting individual airports. The adoption of this rule for dataprocessing constitutes another major contribution of this paper.

Abstract [en]

This paper aims to analyze the GPS traces of 258 volunteers for a better understanding of both the human mobility patterns and the mechanism. We report the regular and scaling properties of human mobility from several aspects, and importantly we identify its levy flight characteristic which is consistent with the previous studies. We further assume two factors that may govern the levy flight property: (1) the scaling and hierarchical properties of the purpose clusters which serve as the underlying spatial structure, and (2) the individual preferential behavior. To verify the assumptions, we implement an agent-based model with the two factors, and the simulated results indeed capture the same levy flight pattern as the observed one. In order to enable the model to reproduce more mobility patterns, we add the model a third factor, the jumping factor which means the probability that one person may cancel the regular mobility schedule and explore a random place. With this factor, our model could cover a relatively wide range of human mobility patterns with scaling exponent values from 1.55 to 2.05.

Tao, Jia

Abstract [en]

Relying on random and purposive moving agents, we simulated human movement in large street networks. We found that aggregate flow, assigned to individual streets, is mainly shaped by the underlying street structure, and that human moving behavior (either random or purposive) has little effect on the aggregate flow. This finding implies that given a street network, the movement patterns generated by purposive walkers (mostly human beings) and by random walkers are the same. Based on the simulation and correlation analysis, we further found that the closeness centrality is not a good indicator for human movement, in contrast to a long-standing view held by space syntax researchers. Instead we suggest that Google's PageRank and its modified version (weighted PageRank), betweenness and degree centralities are all better indicators for predicting aggregate flow.

Abstract [en]

This article provides a new geospatial perspective on whether or not Zipf's law holds for all cities or for the largest cities in the United States using a massive dataset and its computing. A major problem around this issue is how to define cities or city boundaries. Most of the investigations of Zipf's law rely on the demarcations of cities imposed by census data, for example, metropolitan areas and census-designated places. These demarcations or definitions (of cities) are criticized for being subjective or even arbitrary. Alternative solutions to defining cities are suggested, but they still rely on census data for their definitions. In this article we demarcate urban agglomerations by clustering street nodes (including intersections and ends), forming what we call natural cities. Based on the demarcation, we found that Zipf's law holds remarkably well for all the natural cities (over 2-4 million in total) across the United States. There is little sensitivity for the holding with respect to the clustering resolution used for demarcating the natural cities. This is a big contrast to urban areas, as defined in the census data, which do not hold stable for Zipf's law.

Bin, Jiang

Abstract [en]

This paper explores the patterns of human activities within a geographical space by adopting the taxicab static points which refer to the locations with zero speed along the tracking trajectory. We report the findings from both aggregated and individual aspects. Results from the aggregated level indicate the following: (1) Human activities exhibit an obvious regularity in time, for example, there is a burst of activity during weekend nights and a lull during the week. (2) They show a remarkable spatial drifting pattern, which strengthens our understanding of the activities in any given place. (3) Activities are heterogeneous in space irrespective of their drifting with time. These aggregated results not only help in city planning, but also facilitate traffic control and management. On the other hand, investigations on an individual level suggest that (4) activities witnessed by one taxicab will have different temporal regularity to another, and (5) each regularity implies a high level of prediction with low entropy by applying the Lempel-Ziv algorithm.